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IoT 24(1):

Research Article

Empowering Employee Wellness and Building Resilience in Demanding Work Settings Through Predictive Analytics

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  • @ARTICLE{10.4108/eetiot.4644,
        author={Srishti Dikshit and Yashika Grover and Pragati Shukla and Akhil Mishra and Yash Sahu and Chandan Kumar and Muskan Gupta},
        title={Empowering Employee Wellness and Building Resilience in Demanding Work Settings Through Predictive Analytics},
        journal={EAI Endorsed Transactions on Internet of Things},
        volume={10},
        number={1},
        publisher={EAI},
        journal_a={IOT},
        year={2023},
        month={12},
        keywords={Employee Health, stress, prediction, predictive analysis},
        doi={10.4108/eetiot.4644}
    }
    
  • Srishti Dikshit
    Yashika Grover
    Pragati Shukla
    Akhil Mishra
    Yash Sahu
    Chandan Kumar
    Muskan Gupta
    Year: 2023
    Empowering Employee Wellness and Building Resilience in Demanding Work Settings Through Predictive Analytics
    IOT
    EAI
    DOI: 10.4108/eetiot.4644
Srishti Dikshit1,*, Yashika Grover2, Pragati Shukla1, Akhil Mishra1, Yash Sahu1, Chandan Kumar1, Muskan Gupta1
  • 1: Noida Institute of Engineering and Technology
  • 2: HSBC
*Contact email: srishti.dikshit@niet.co.in

Abstract

In today's fast-paced and competitive corporate landscape, the well-being of employees is paramount for sustained success. This paper explores the transformative potential of predictive analytics in cultivating a healthier, more resilient workforce within high-pressure work environments. The title "Empowering Employee Wellness and Building Resilience in Demanding Work Settings Through Predictive Analytics" encapsulates our objective of harnessing data-driven insights to mitigate the negative effects of high-pressure work settings and foster an environment where employees thrive. Through an in-depth examination of predictive analytics tools and methodologies, this study offers a roadmap for organizations to proactively identify stressors, predict burnout risks, and implement targeted interventions. By collecting and analysing relevant data, employers can tailor support systems, optimize workloads, and implement mindfulness programs that enhance employee well-being. Moreover, organizations can better adapt to change, maintain workforce continuity, and drive productivity by fostering resilience through predictive insights. This research bridges the gap between data science and human resources, offering a holistic approach to employee wellness and resilience-building. By leveraging predictive analytics, companies can create a culture of care where employees feel supported, empowered, and more capable of surviving and thriving in high-pressure work environments.

Keywords
Employee Health, stress, prediction, predictive analysis
Received
2023-10-14
Accepted
2023-12-11
Published
2023-12-19
Publisher
EAI
http://dx.doi.org/10.4108/eetiot.4644

Copyright © 2023 S. Dikshit et al., licensed to EAI. This is an open-access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.

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